Evidence map›Paper›PMID 40715674›Full record

ArticleEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2025

Segmentation-based 3D volumetry and linear regression modeling for assessing the vertebral bone loss in pyogenic vertebral osteomyelitis.

Siegmund Lang, Michael Bachtler, Josina Straub, Jonas Krückel, Susanne Baertl, Melanie Ardelt, Gerardo Napodano, Michael Haimerl, Markus Loibl, Volker Alt and 1 more

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Article in European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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5 · Who and what money

Authors and funding

11 authors.

Siegmund LangDepartment of Trauma Surgery, University Medical Center Regensburg, Regensburg, Germany. Siegmund.Lang@ukr.de.
Michael BachtlerDepartment of Trauma Surgery, University Medical Center Regensburg, Regensburg, Germany.
Josina StraubDepartment of Trauma Surgery, University Medical Center Regensburg, Regensburg, Germany.
Jonas KrückelDepartment of Trauma Surgery, University Medical Center Regensburg, Regensburg, Germany.
Susanne BaertlDepartment of Trauma Surgery, University Medical Center Regensburg, Regensburg, Germany.
Melanie ArdeltDepartment of Orthopaedics and Trauma Surgery, University Hospital Krems, Karl Landsteiner University of Health Sciences, Krems, Austria.
Gerardo NapodanoInstitute of Radiology, University Hospital Regensburg, Regensburg, Germany.
Michael HaimerlDepartment of Radiology, Klinikum Würzburg Mitte, Wurzburg, Germany.
Markus LoiblDepartment of Spine Surgery, Schulthess Clinic, Zurich, Switzerland.
Volker AltDepartment of Trauma Surgery, University Medical Center Regensburg, Regensburg, Germany.
Maximilian KerschbaumDepartment of Trauma Surgery, University Medical Center Regensburg, Regensburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPyogenic vertebral osteomyelitis (PVO) presents an escalating clinical challenge due to rising incidence, high mortality, and significant bone destruction. Objective quantification of vertebral body (VB) bone loss for assessing the disease severity and guiding therapeutic decisions is yet to be established.

methodsWe retrospectively identified patients with confirmed PVO between 2010 and 2020. Volumetric assessments of VBs were performed using 3D Slicer, and pre-infection volumes were estimated by linear regression based on adjacent, non-infected vertebrae. A "Destruction Quotient" (DQ) was calculated (measured volume/estimated original volume) to quantify VB loss. In a subgroup analysis VB bone loss was evaluated, depending on sex, spinal location and pathogen group.

resultsThirty-one patients met the inclusion criteria for 3D volumetry (16 males, 15 females; mean age: 67.0 ± 9.2 years; mean BMI 32.4 kg/m²). In total, n = 267 VBs were segmented. Linear regression models demonstrated a high mean coefficient of determination (R²>0.95), with mean slopes of m = 2.3 (95% CI = 1.94-2.75) in males and m = 1.8 (95% CI = 1.46-2.19) in females. The mean measured volume of infected VBs (17.8 ± 9.3 cm³) was significantly lower than the estimated original volume (24.1 ± 10.5 cm³; p < 0.001). VBs at the lumbar spine experienced a median volume loss of 30%, whereas thoracic VBs showed 18% loss of volume. Female patients demonstrated a significantly higher median VB loss (32%) than males (12%; p < 0.05). No significant variation in DQs was observed among different pathogen groups, with Staphylococcus aureus being the most prevalent; however, within the Staphylococcus aureus subgroup, the measured VB volume was significantly smaller than the original estimated volume with a mean difference of 6.13 ± 4.9 cm

conclusionA 3D-volumetric approach and linear regression modeling offers an individualized method for quantifying VB destruction in PVO. Integrating automated segmentation and densitometric data may further enhance predictive accuracy and improve patient-specific treatment strategies.

Indexed as

Imaging, Three-DimensionalOsteomyelitisSpinal DiseasesVertebral BodyAgedAged, 80 and overFemaleHumansLinear ModelsMagnetic Resonance ImagingMaleMiddle AgedRetrospective StudiesTomography, X-Ray Computed3D-VolumetrySegmentationSpinal infectionsSpondylodiscitisVertebral osteomyelitis

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.